Shadow is a common physical phenomenon in nature, and is generated when a light source is blocked by an object. A shadow in an image has different effects on related issues in the field of computer vision, including positive and negative effects. For example, adding shadows to objects in virtual reality and 3D games can improve the sense of reality of a scene, but in more cases, a shadow in an image has a negative effect on related issues in computer vision. For example, in a remote sensing image, a shadow affects many subsequent processing operations on the remote sensing image, such as image matching, pattern recognition, and surface feature extraction. In video surveillance, the combination of a shadow and a moving target results in an error when the computer extracts and tracks the target object. Therefore, it is necessary to detect and analyze a shadow in an image, and further eliminate or reduce the effect of the shadow as required.
At present, many experts and scholars around the world have conducted intensive research on elimination of shadow in video, and have proposed many effective algorithms. These algorithms are widely applied in fields such as video surveillance and vehicle tracking, but cannot be used to process static images. Shadow detection in a static image has always been a difficult problem, because the static image contains less information, and a shadow therein cannot be detected by using an inter-frame relationship, which is used to detect shadows in video. Meanwhile, in research fields based on a static image, such as remote sensing imaging, after a shadow is detected, influence of the shadow further needs to be reduced or eliminated as far as possible, to recover original features of an object in the shadow, so as to improve the authenticity of an infrared remote sensing image.
At present, there is no related report on detecting a zonal underground structure, such as an underground river or an underground tunnel, by using the infrared imaging technology around the world. A shadow in an infrared remote sensing image increases the false alarm rate in zonal underground structure detection, and reduces the detectivity.